// This file is part of Eigen, a lightweight C++ template library
// for linear algebra.
//
// Copyright (C) 2006-2008 Benoit Jacob <jacob.benoit.1@gmail.com>
// Copyright (C) 2009-2014 Gael Guennebaud <gael.guennebaud@inria.fr>
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
// with this file, You can obtain one at http://mozilla.org/MPL/2.0/.

#ifndef EIGEN_TRANSPOSE_H
#define EIGEN_TRANSPOSE_H

namespace Eigen {

namespace internal {
template<typename MatrixType>
struct traits<Transpose<MatrixType>> : public traits<MatrixType>
{
	typedef typename ref_selector<MatrixType>::type MatrixTypeNested;
	typedef typename remove_reference<MatrixTypeNested>::type MatrixTypeNestedPlain;
	enum
	{
		RowsAtCompileTime = MatrixType::ColsAtCompileTime,
		ColsAtCompileTime = MatrixType::RowsAtCompileTime,
		MaxRowsAtCompileTime = MatrixType::MaxColsAtCompileTime,
		MaxColsAtCompileTime = MatrixType::MaxRowsAtCompileTime,
		FlagsLvalueBit = is_lvalue<MatrixType>::value ? LvalueBit : 0,
		Flags0 = traits<MatrixTypeNestedPlain>::Flags & ~(LvalueBit | NestByRefBit),
		Flags1 = Flags0 | FlagsLvalueBit,
		Flags = Flags1 ^ RowMajorBit,
		InnerStrideAtCompileTime = inner_stride_at_compile_time<MatrixType>::ret,
		OuterStrideAtCompileTime = outer_stride_at_compile_time<MatrixType>::ret
	};
};
}

template<typename MatrixType, typename StorageKind>
class TransposeImpl;

/** \class Transpose
 * \ingroup Core_Module
 *
 * \brief Expression of the transpose of a matrix
 *
 * \tparam MatrixType the type of the object of which we are taking the transpose
 *
 * This class represents an expression of the transpose of a matrix.
 * It is the return type of MatrixBase::transpose() and MatrixBase::adjoint()
 * and most of the time this is the only way it is used.
 *
 * \sa MatrixBase::transpose(), MatrixBase::adjoint()
 */
template<typename MatrixType>
class Transpose : public TransposeImpl<MatrixType, typename internal::traits<MatrixType>::StorageKind>
{
  public:
	typedef typename internal::ref_selector<MatrixType>::non_const_type MatrixTypeNested;

	typedef typename TransposeImpl<MatrixType, typename internal::traits<MatrixType>::StorageKind>::Base Base;
	EIGEN_GENERIC_PUBLIC_INTERFACE(Transpose)
	typedef typename internal::remove_all<MatrixType>::type NestedExpression;

	EIGEN_DEVICE_FUNC
	explicit EIGEN_STRONG_INLINE Transpose(MatrixType& matrix)
		: m_matrix(matrix)
	{
	}

	EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Transpose)

	EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EIGEN_CONSTEXPR Index rows() const EIGEN_NOEXCEPT { return m_matrix.cols(); }
	EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EIGEN_CONSTEXPR Index cols() const EIGEN_NOEXCEPT { return m_matrix.rows(); }

	/** \returns the nested expression */
	EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename internal::remove_all<MatrixTypeNested>::type&
	nestedExpression() const
	{
		return m_matrix;
	}

	/** \returns the nested expression */
	EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::remove_reference<MatrixTypeNested>::type&
	nestedExpression()
	{
		return m_matrix;
	}

	/** \internal */
	EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void resize(Index nrows, Index ncols) { m_matrix.resize(ncols, nrows); }

  protected:
	typename internal::ref_selector<MatrixType>::non_const_type m_matrix;
};

namespace internal {

template<typename MatrixType, bool HasDirectAccess = has_direct_access<MatrixType>::ret>
struct TransposeImpl_base
{
	typedef typename dense_xpr_base<Transpose<MatrixType>>::type type;
};

template<typename MatrixType>
struct TransposeImpl_base<MatrixType, false>
{
	typedef typename dense_xpr_base<Transpose<MatrixType>>::type type;
};

} // end namespace internal

// Generic API dispatcher
template<typename XprType, typename StorageKind>
class TransposeImpl : public internal::generic_xpr_base<Transpose<XprType>>::type
{
  public:
	typedef typename internal::generic_xpr_base<Transpose<XprType>>::type Base;
};

template<typename MatrixType>
class TransposeImpl<MatrixType, Dense> : public internal::TransposeImpl_base<MatrixType>::type
{
  public:
	typedef typename internal::TransposeImpl_base<MatrixType>::type Base;
	using Base::coeffRef;
	EIGEN_DENSE_PUBLIC_INTERFACE(Transpose<MatrixType>)
	EIGEN_INHERIT_ASSIGNMENT_OPERATORS(TransposeImpl)

	EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index innerStride() const
	{
		return derived().nestedExpression().innerStride();
	}
	EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index outerStride() const
	{
		return derived().nestedExpression().outerStride();
	}

	typedef typename internal::conditional<internal::is_lvalue<MatrixType>::value, Scalar, const Scalar>::type
		ScalarWithConstIfNotLvalue;

	EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ScalarWithConstIfNotLvalue* data()
	{
		return derived().nestedExpression().data();
	}
	EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar* data() const { return derived().nestedExpression().data(); }

	// FIXME: shall we keep the const version of coeffRef?
	EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeffRef(Index rowId, Index colId) const
	{
		return derived().nestedExpression().coeffRef(colId, rowId);
	}

	EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeffRef(Index index) const
	{
		return derived().nestedExpression().coeffRef(index);
	}

  protected:
	EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(TransposeImpl)
};

/** \returns an expression of the transpose of *this.
 *
 * Example: \include MatrixBase_transpose.cpp
 * Output: \verbinclude MatrixBase_transpose.out
 *
 * \warning If you want to replace a matrix by its own transpose, do \b NOT do this:
 * \code
 * m = m.transpose(); // bug!!! caused by aliasing effect
 * \endcode
 * Instead, use the transposeInPlace() method:
 * \code
 * m.transposeInPlace();
 * \endcode
 * which gives Eigen good opportunities for optimization, or alternatively you can also do:
 * \code
 * m = m.transpose().eval();
 * \endcode
 *
 * \sa transposeInPlace(), adjoint() */
template<typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Transpose<Derived>
DenseBase<Derived>::transpose()
{
	return TransposeReturnType(derived());
}

/** This is the const version of transpose().
 *
 * Make sure you read the warning for transpose() !
 *
 * \sa transposeInPlace(), adjoint() */
template<typename Derived>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename DenseBase<Derived>::ConstTransposeReturnType
DenseBase<Derived>::transpose() const
{
	return ConstTransposeReturnType(derived());
}

/** \returns an expression of the adjoint (i.e. conjugate transpose) of *this.
 *
 * Example: \include MatrixBase_adjoint.cpp
 * Output: \verbinclude MatrixBase_adjoint.out
 *
 * \warning If you want to replace a matrix by its own adjoint, do \b NOT do this:
 * \code
 * m = m.adjoint(); // bug!!! caused by aliasing effect
 * \endcode
 * Instead, use the adjointInPlace() method:
 * \code
 * m.adjointInPlace();
 * \endcode
 * which gives Eigen good opportunities for optimization, or alternatively you can also do:
 * \code
 * m = m.adjoint().eval();
 * \endcode
 *
 * \sa adjointInPlace(), transpose(), conjugate(), class Transpose, class internal::scalar_conjugate_op */
template<typename Derived>
EIGEN_DEVICE_FUNC inline const typename MatrixBase<Derived>::AdjointReturnType
MatrixBase<Derived>::adjoint() const
{
	return AdjointReturnType(this->transpose());
}

/***************************************************************************
 * "in place" transpose implementation
 ***************************************************************************/

namespace internal {

template<typename MatrixType,
		 bool IsSquare = (MatrixType::RowsAtCompileTime == MatrixType::ColsAtCompileTime) &&
						 MatrixType::RowsAtCompileTime != Dynamic,
		 bool MatchPacketSize =
			 (int(MatrixType::RowsAtCompileTime) == int(internal::packet_traits<typename MatrixType::Scalar>::size)) &&
			 (internal::evaluator<MatrixType>::Flags & PacketAccessBit)>
struct inplace_transpose_selector;

template<typename MatrixType>
struct inplace_transpose_selector<MatrixType, true, false>
{ // square matrix
	static void run(MatrixType& m)
	{
		m.matrix().template triangularView<StrictlyUpper>().swap(
			m.matrix().transpose().template triangularView<StrictlyUpper>());
	}
};

template<typename MatrixType>
struct inplace_transpose_selector<MatrixType, true, true>
{ // PacketSize x PacketSize
	static void run(MatrixType& m)
	{
		typedef typename MatrixType::Scalar Scalar;
		typedef typename internal::packet_traits<typename MatrixType::Scalar>::type Packet;
		const Index PacketSize = internal::packet_traits<Scalar>::size;
		const Index Alignment = internal::evaluator<MatrixType>::Alignment;
		PacketBlock<Packet> A;
		for (Index i = 0; i < PacketSize; ++i)
			A.packet[i] = m.template packetByOuterInner<Alignment>(i, 0);
		internal::ptranspose(A);
		for (Index i = 0; i < PacketSize; ++i)
			m.template writePacket<Alignment>(m.rowIndexByOuterInner(i, 0), m.colIndexByOuterInner(i, 0), A.packet[i]);
	}
};

template<typename MatrixType, Index Alignment>
void
BlockedInPlaceTranspose(MatrixType& m)
{
	typedef typename MatrixType::Scalar Scalar;
	typedef typename internal::packet_traits<typename MatrixType::Scalar>::type Packet;
	const Index PacketSize = internal::packet_traits<Scalar>::size;
	eigen_assert(m.rows() == m.cols());
	int row_start = 0;
	for (; row_start + PacketSize <= m.rows(); row_start += PacketSize) {
		for (int col_start = row_start; col_start + PacketSize <= m.cols(); col_start += PacketSize) {
			PacketBlock<Packet> A;
			if (row_start == col_start) {
				for (Index i = 0; i < PacketSize; ++i)
					A.packet[i] = m.template packetByOuterInner<Alignment>(row_start + i, col_start);
				internal::ptranspose(A);
				for (Index i = 0; i < PacketSize; ++i)
					m.template writePacket<Alignment>(m.rowIndexByOuterInner(row_start + i, col_start),
													  m.colIndexByOuterInner(row_start + i, col_start),
													  A.packet[i]);
			} else {
				PacketBlock<Packet> B;
				for (Index i = 0; i < PacketSize; ++i) {
					A.packet[i] = m.template packetByOuterInner<Alignment>(row_start + i, col_start);
					B.packet[i] = m.template packetByOuterInner<Alignment>(col_start + i, row_start);
				}
				internal::ptranspose(A);
				internal::ptranspose(B);
				for (Index i = 0; i < PacketSize; ++i) {
					m.template writePacket<Alignment>(m.rowIndexByOuterInner(row_start + i, col_start),
													  m.colIndexByOuterInner(row_start + i, col_start),
													  B.packet[i]);
					m.template writePacket<Alignment>(m.rowIndexByOuterInner(col_start + i, row_start),
													  m.colIndexByOuterInner(col_start + i, row_start),
													  A.packet[i]);
				}
			}
		}
	}
	for (Index row = row_start; row < m.rows(); ++row) {
		m.matrix().row(row).head(row).swap(m.matrix().col(row).head(row).transpose());
	}
}

template<typename MatrixType, bool MatchPacketSize>
struct inplace_transpose_selector<MatrixType, false, MatchPacketSize>
{ // non square or dynamic matrix
	static void run(MatrixType& m)
	{
		typedef typename MatrixType::Scalar Scalar;
		if (m.rows() == m.cols()) {
			const Index PacketSize = internal::packet_traits<Scalar>::size;
			if (!NumTraits<Scalar>::IsComplex && m.rows() >= PacketSize) {
				if ((m.rows() % PacketSize) == 0)
					BlockedInPlaceTranspose<MatrixType, internal::evaluator<MatrixType>::Alignment>(m);
				else
					BlockedInPlaceTranspose<MatrixType, Unaligned>(m);
			} else {
				m.matrix().template triangularView<StrictlyUpper>().swap(
					m.matrix().transpose().template triangularView<StrictlyUpper>());
			}
		} else {
			m = m.transpose().eval();
		}
	}
};

} // end namespace internal

/** This is the "in place" version of transpose(): it replaces \c *this by its own transpose.
 * Thus, doing
 * \code
 * m.transposeInPlace();
 * \endcode
 * has the same effect on m as doing
 * \code
 * m = m.transpose().eval();
 * \endcode
 * and is faster and also safer because in the latter line of code, forgetting the eval() results
 * in a bug caused by \ref TopicAliasing "aliasing".
 *
 * Notice however that this method is only useful if you want to replace a matrix by its own transpose.
 * If you just need the transpose of a matrix, use transpose().
 *
 * \note if the matrix is not square, then \c *this must be a resizable matrix.
 * This excludes (non-square) fixed-size matrices, block-expressions and maps.
 *
 * \sa transpose(), adjoint(), adjointInPlace() */
template<typename Derived>
EIGEN_DEVICE_FUNC inline void
DenseBase<Derived>::transposeInPlace()
{
	eigen_assert((rows() == cols() || (RowsAtCompileTime == Dynamic && ColsAtCompileTime == Dynamic)) &&
				 "transposeInPlace() called on a non-square non-resizable matrix");
	internal::inplace_transpose_selector<Derived>::run(derived());
}

/***************************************************************************
 * "in place" adjoint implementation
 ***************************************************************************/

/** This is the "in place" version of adjoint(): it replaces \c *this by its own transpose.
 * Thus, doing
 * \code
 * m.adjointInPlace();
 * \endcode
 * has the same effect on m as doing
 * \code
 * m = m.adjoint().eval();
 * \endcode
 * and is faster and also safer because in the latter line of code, forgetting the eval() results
 * in a bug caused by aliasing.
 *
 * Notice however that this method is only useful if you want to replace a matrix by its own adjoint.
 * If you just need the adjoint of a matrix, use adjoint().
 *
 * \note if the matrix is not square, then \c *this must be a resizable matrix.
 * This excludes (non-square) fixed-size matrices, block-expressions and maps.
 *
 * \sa transpose(), adjoint(), transposeInPlace() */
template<typename Derived>
EIGEN_DEVICE_FUNC inline void
MatrixBase<Derived>::adjointInPlace()
{
	derived() = adjoint().eval();
}

#ifndef EIGEN_NO_DEBUG

// The following is to detect aliasing problems in most common cases.

namespace internal {

template<bool DestIsTransposed, typename OtherDerived>
struct check_transpose_aliasing_compile_time_selector
{
	enum
	{
		ret = bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed
	};
};

template<bool DestIsTransposed, typename BinOp, typename DerivedA, typename DerivedB>
struct check_transpose_aliasing_compile_time_selector<DestIsTransposed, CwiseBinaryOp<BinOp, DerivedA, DerivedB>>
{
	enum
	{
		ret = bool(blas_traits<DerivedA>::IsTransposed) != DestIsTransposed ||
			  bool(blas_traits<DerivedB>::IsTransposed) != DestIsTransposed
	};
};

template<typename Scalar, bool DestIsTransposed, typename OtherDerived>
struct check_transpose_aliasing_run_time_selector
{
	static bool run(const Scalar* dest, const OtherDerived& src)
	{
		return (bool(blas_traits<OtherDerived>::IsTransposed) != DestIsTransposed) &&
			   (dest != 0 && dest == (const Scalar*)extract_data(src));
	}
};

template<typename Scalar, bool DestIsTransposed, typename BinOp, typename DerivedA, typename DerivedB>
struct check_transpose_aliasing_run_time_selector<Scalar, DestIsTransposed, CwiseBinaryOp<BinOp, DerivedA, DerivedB>>
{
	static bool run(const Scalar* dest, const CwiseBinaryOp<BinOp, DerivedA, DerivedB>& src)
	{
		return ((blas_traits<DerivedA>::IsTransposed != DestIsTransposed) &&
				(dest != 0 && dest == (const Scalar*)extract_data(src.lhs()))) ||
			   ((blas_traits<DerivedB>::IsTransposed != DestIsTransposed) &&
				(dest != 0 && dest == (const Scalar*)extract_data(src.rhs())));
	}
};

// the following selector, checkTransposeAliasing_impl, based on MightHaveTransposeAliasing,
// is because when the condition controlling the assert is known at compile time, ICC emits a warning.
// This is actually a good warning: in expressions that don't have any transposing, the condition is
// known at compile time to be false, and using that, we can avoid generating the code of the assert again
// and again for all these expressions that don't need it.

template<typename Derived,
		 typename OtherDerived,
		 bool MightHaveTransposeAliasing =
			 check_transpose_aliasing_compile_time_selector<blas_traits<Derived>::IsTransposed, OtherDerived>::ret>
struct checkTransposeAliasing_impl
{
	static void run(const Derived& dst, const OtherDerived& other)
	{
		eigen_assert((!check_transpose_aliasing_run_time_selector<typename Derived::Scalar,
																  blas_traits<Derived>::IsTransposed,
																  OtherDerived>::run(extract_data(dst), other)) &&
					 "aliasing detected during transposition, use transposeInPlace() "
					 "or evaluate the rhs into a temporary using .eval()");
	}
};

template<typename Derived, typename OtherDerived>
struct checkTransposeAliasing_impl<Derived, OtherDerived, false>
{
	static void run(const Derived&, const OtherDerived&) {}
};

template<typename Dst, typename Src>
void
check_for_aliasing(const Dst& dst, const Src& src)
{
	if ((!Dst::IsVectorAtCompileTime) && dst.rows() > 1 && dst.cols() > 1)
		internal::checkTransposeAliasing_impl<Dst, Src>::run(dst, src);
}

} // end namespace internal

#endif // EIGEN_NO_DEBUG

} // end namespace Eigen

#endif // EIGEN_TRANSPOSE_H
